1. Field of the Invention
The present invention is related generally to an improved data processing system and in particular to a method and apparatus for processing video and audio data. More particularly, the present invention is directed to a computer implemented method, apparatus, and computer usable program code for using biometric data for a customer to generate customized marketing messages promoting upsales and cross-sales of items.
2. Description of the Related Art
When a customer shows interest in purchasing a particular item, merchants frequently attempt to induce the customer to purchase a more expensive brand of the item, an upgraded version of the item, a larger and more expensive size of the item, and/or other additions and special features for the item to make the sale more profitable. These sales techniques are sometimes referred to as upselling or upsale. For example, if a user is interested in purchasing a used car, the salesman may attempt to induce the customer into purchasing a more expensive new car instead. If the salesman is successful, the upsale of the more expensive car will likely generate greater profit and/or greater revenue.
Another sales technique involves selling related products to customers to increase profit and/or revenue. For example, if a customer shows interest in purchasing a bicycle, the salesman may attempt to induce the customer into purchasing a bicycle helmet, a bicycle tire pump, a spare tire, an extra bicycle chain, and/or other items that might be used in conjunction with the bicycle. This sales technique is referred to as cross-selling.
In the past, merchants, such as store owners and operators, frequently had a personal relationship with their customers. The merchant often knew their customers' names, address, marital status, ages of their children, hobbies, place of employment, anniversaries, birthdays, likes, dislikes and personal preferences. The merchant was able to use this information to cater to customer needs and push upsales and cross-sales of items the customer might be likely to purchase based on the customer's personal situation and the merchant's personal knowledge of purchases by his customers.
However, with the continued growth of large cities, the corresponding disappearance of small, rural towns, and the increasing number of large, impersonal chain stores with multiple employees, the merchants and employees of retail businesses rarely recognize regular customers, and almost never know the customer's name or any other details regarding their customer's personal preferences that might assist the merchant or employee in marketing efforts directed toward a particular customer.
One solution to this problem is directed toward using profile data for a customer to generate marketing messages that may be sent to the customer by email, print media, telephone, or over the World Wide Web via a web page. Customer profile data typically includes information provided by the customer in response to a questionnaire or survey, such as name, address, telephone number, gender, and indicators of particular products the customer is interested in purchasing. Demographic data regarding a customer's age, sex, income, career, interests, hobbies, and consumer preferences may also be included in customer profile data.
Advertising computers can generate a customer advertisement based on the customer's static profile. However, this method only provides a small number of pre-generated advertisements that are directed towards a fairly large segment of the population rather than to one individual.
In another solution, user profile data, demographic data, point of contact data, and transaction data are analyzed to generate advertising content for customers that target the information content presented to individual consumers or users to increase the likelihood that the customer will purchase the goods or services presented. Current solutions do not utilize all of the potential customer data elements that may be available to a retail owner or operator for generating customized marketing messages targeted to individual customers. Other data pieces are needed to provide effective dynamic one-to-one marketing of messages to the potential customer. Therefore, the data elements in prior art only provides approximately seventy-five percent (75%) of the needed data.